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Spectral Clustering by Subspace Randomization and Graph Fusion for High-Dimensional Data

Subspace clustering has been gaining increasing attention in recent years due to its promising ability in dealing with high-dimensional data. However, most of the existing subspace clustering methods tend to only exploit the subspace information to construct a single affinity graph (typically for sp...

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Detalhes bibliográficos
Publicado no:Advances in Knowledge Discovery and Data Mining
Main Authors: Cai, Xiaosha, Huang, Dong, Wang, Chang-Dong, Kwoh, Chee-Keong
Formato: Artigo
Idioma:Inglês
Publicado em: 2020
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Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7206270/
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-47426-3_26
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